In order to learn complex scientific concepts and practices, students build virtual and physical models of scientific phenomena and connected them in real time.
Bifocal Modeling is a new framework for inquiry-driven science learning. It challenges students to build and relate in real-time experiments and models. In these activities, students explore a scientific phenomenon such as heat diffusion, properties of gases, or wave propagation by designing an experiment and a model and connecting them in real time. For instance, during the physical experiment, students design and develop their own experiment and collect data using embedded sensors. In parallel, they design and develop a virtual model of the same phenomenon, their goal is to build a virtual model which behavior matches the physical data they collected, so they compare the behavior of the virtual model and the physical model in real-time.
Bifocal Modeling includes various distinctive sub-activities as described in the figure below (Blikstein et al. 2012).
Different ways of resource allocation among these sub-activities could yield to various modes of implementation.
A. Design - Students were encouraged to use external learning resources, such as the web or books, to gather initial information about the phenomenon. Students select questions they would like to answer, generate hypotheses about what they will observe, and design physical experiment and virtual model that can potentially answer those hypotheses. In designing the virtual model, students typically define the possible variables, and conceptualize micro-rules or equations to describe the phenomenon.
B. Construct - Students construct structure of their physical experiment (e.g. a ball and ramp) and virtual model (e.g. a computer model of a ball rolling down a ramp) that will capture the phenomena under study.
C. Interact - Students gather data from their physical models using embedded sensors. Similarly, they gather data from the virtual model by changing parameters, running the model, observing the results, and recording data.
Bifocal Modeling encourages students to refine their content knowledge as they iteratively improve their models, and to question the validity of their own representational choices.